Many Molecular Properties from One Kernel in Chemical Space by Raghunathan Ramakrishnan, O. Anatole von Lilienfeld

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Retrospective on a decade of machine learning for chemical discovery by O. Anatole von Lilienfeld, Kieron Burke

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Operator Quantum Machine Learning: Navigating the Chemical Space of Response Properties by Anders S. Christensen, O. Anatole von Lilienfeld

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Alchemical perturbation density functional theory by Guido Falk von Rudorff, O. Anatole von Lilienfeld

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Quantum Mechanical Treatment of Variable Molecular Composition: From 'Alchemical' Changes of State Functions to Rational Compound Design by K. Y. Samuel Chang, O. Anatole von Lilienfeld

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Encrypted machine learning of molecular quantum properties by Jan Weinreich, Guido Falk von Rudorff, O Anatole von Lilienfeld

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Autonomous data extraction from peer reviewed literature for training machine learning models of oxidation potentials by Siwoo Lee, Stefan Heinen, Danish Khan, O Anatole von Lilienfeld

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Improved decision making with similarity based machine learning: applications in chemistry by Dominik Lemm, Guido Falk von Rudorff, O Anatole von Lilienfeld

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Conformer-specific polar cycloaddition of dibromobutadiene with trapped propene ions by Ardita Kilaj, Jia Wang, Patrik Straňák, Max Schwilk, Uxía Rivero, Lei Xu, O. Anatole von Lilienfeld, Jochen Küpper, Stefan Willitsch

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Machine learning of molecular electronic properties in chemical compound space by Grégoire Montavon, Matthias Rupp, Vivekanand Gobre, Alvaro Vazquez-Mayagoitia, Katja Hansen, Alexandre Tkatchenko, Klaus-Robert Müller, O Anatole von Lilienfeld

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